Job Description
We are at the precipice of a new technological era. Apex Horizon Labs is seeking a visionary Future-Proof AI Architect to lead the development of next-generation generative models that will define the industry landscape in 2026 and beyond. You won't just be building models; you will be architecting the intelligence of tomorrow.
In this role, you will bridge the gap between theoretical AI research and scalable production systems. You will work with a world-class team of data scientists, engineers, and ethicists to push the boundaries of what Artificial General Intelligence (AGI) can achieve. If you are passionate about solving complex problems and want to leave a lasting legacy in the tech world, we want to meet you.
Why Join Us?
- Work on cutting-edge projects with a competitive salary and equity package.
- Flexible remote-first hybrid policy with a premium office in the heart of SF.
- Access to state-of-the-art computing resources and research grants.
Responsibilities
- Architect Future-Proof Systems: Design and implement robust, scalable AI architectures capable of handling the demands of 2026 and future technological shifts.
- Lead R&D Initiatives: Spearhead research in Large Language Models (LLMs), Computer Vision, and Reinforcement Learning to achieve state-of-the-art performance.
- Model Optimization: Optimize model inference speeds and reduce latency to ensure real-time user experiences across all platforms.
- Ethical AI Governance: Establish and enforce protocols for AI safety, bias mitigation, and transparency in all automated systems.
- Technical Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Collaboration: Partner with product managers and stakeholders to translate complex technical concepts into actionable business strategies.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in building, deploying, and scaling machine learning models in production environments.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of distributed computing systems (Kubernetes, Docker).
- Expertise: Strong background in Natural Language Processing (NLP) or Computer Vision with a portfolio of published research or deployed products.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and derive innovative solutions under tight deadlines.
- Communication: Excellent verbal and written communication skills, capable of presenting complex technical ideas to non-technical audiences.